Marten van Dijk
Artificial Intelligence · 1998–2021
A researcher in the Science corpus: 12 papers; trusts 62 researchers and is trusted by 46 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 80 citations into it; #5,564 of 35,345 by trust here, #5,084 by citations
- Optimization & Training — 55 citations into it; #1,879 of 2,601 by trust here, #1,624 by citations
- Computational Mechanics — 30 citations into it
- Computer Vision and Pattern Recognition — 26 citations into it; #5,684 of 21,575 by trust here, #5,507 by citations
- Safety, Robustness & Interpretability — 15 citations into it
- Computational Theory and Mathematics — 13 citations into it; #10,280 of 12,182 by trust here, #4,850 by citations
- Management Science and Operations Research — 13 citations into it
- Signal Processing — 12 citations into it; #2,511 of 7,572 by trust here, #1,709 by citations
Whom Marten van Dijk trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Craig Gentry
- L. Eon Bottou
- Dimitri P. Bertsekas
- Alex Krizhevsky
- Geoffrey E. Hinton
- Yurii E. Nesterov
- Yann LeCun
- Francis R. Bach
- Diederik P. Kingma
- Yoshua Bengio
Who trusts Marten van Dijk overall
- Craig Gentry
- Zvika Brakerski
- Shai Halevi
- Jean-Sébastien Coron
- Prastudy Fauzi
- G. Suh
- Vinod Vaikuntanathan
- Jung Hee Cheon
- Ciara Moore
- Wenxiu Ding
Papers from Marten van Dijk's perspective
Ordered by how strongly the researchers Marten van Dijk trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Fully Homomorphic Encryption over the Integers (2010) — 1,938 citations
- SGD and Hogwild! Convergence Without the Bounded Gradients Assumption (2018) — 251 citations
- Extracting secret keys from integrated circuits (2005) — 1,048 citations
- A technique to build a secret key in integrated circuits for identification and authentication applications (2004) — 877 citations
- Efficient memory integrity verification and encryption for secure processors (2003) — 305 citations
- On the Robustness of Vision Transformers to Adversarial Examples (2021) — 270 citations
- A Unified Convergence Analysis for Shuffling-Type Gradient Methods (2020) — 100 citations
- New Convergence Aspects of Stochastic Gradient Algorithms (2018) — 78 citations
- Caches and hash trees for efficient memory integrity verification (2003) — 296 citations
- AEGIS: architecture for tamper-evident and tamper-resistant processing (2003) — 619 citations
- Controlled physical random functions (2002) — 450 citations
- Analysis of the Sensitivity Attack against Electronic Watermarks in Images (1998)